Spatio-temporal characteristics of acoustic emission during the deformation of rock samples with compressional and extensional en-echelon faults

The spatio-temporal characteristics of acoustic emission (AE) during the deformation of rock samples with compressional and extensional en-echelon faults have been studied. The results show that the pre-existing structure can significantly influence the patterns of AE spatial distribution. With increasing of differential stress, AE events firstly cluster around the two ends of pre-existing faults inside the jog and then along the line joining the two ends. The biggish AE events often occur around one end repeatedly. The image of AE clusters indicates the direction and the area of the fracture propagation. The direction of the macroscopic fracture in extensional and compressional jogs is perpendicular and parallel to the direction of axial stress, respectively. The weakening process before the fracturing of jog area is remarkable, and one of the typical precursors for the instability is that the cumulative frequency of AE events increases exponentially. After the fracturing of the jog the frequency and releasing strain energy of AE events decrease gradually. During the friction period, there is no precursory increasing of AE activity before the big stick-slip events. The change of b value in jog shows a typical change of decreasing tendentiously returning quickly before the instability. The decrease of b value occurs in the process of stress increasing and sometime goes down to the weakening stage, and the quick increase b values appears in a short time just before the instability. The comparative analysis shows that the difference in b value due to the different structures is larger than b value variation caused by increase of the differential stress. For the same sample, the temporal sequence of AE is strongly affected by the mechanical state, and the high loading velocity corresponds to the high release rate of strain energy and low b value. Due to its lower failure strength, the broken area is sensitive to small changes in differential stress. Therefore, it offers a potential explanation for the phenomena of precursory window or sensitive point and separation of seismic source and precursors.

Compressional Wave Velocities in Some Volcanic Rocks at Pressure up to 4.5 GPa

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Appraisal of CO2 storage potential in compressional hydrocarbon-bearing basins: Global assessment and case study in the Sichuan Basin(China)

Carbon capture and storage(CCS)has been proposed as a potential technology to mitigate climate change.However,there is currently a huge gap between the current global deployment of this technology and that which will be ultimately required.Whilst CO2 can be captured at any geographic location,storage of CO2 will be constrained by the geological storage potential in the area the CO2 is captured.The geological storage potential can be evaluated at a very high level according to the tectonic setting of the target area.To date,CCS deployment has been restricted to more favourable tectonic settings,such as extensional passive margin and post-rift basins and compressional foreland basins.However,to reach the adequate level of deployment,the potential for CCS of regions in different tectonic settings needs to be explored and assessed worldwide.Surprisingly,the potential of compressional basins for carbon storage has not been universally evaluated according to the global and regional carbon emission distribution.Here,we present an integrated source-to-sink analysis tool that combines comprehensive,open-access information on basin distribution,hydrocarbon resources and CO2 emissions based on geographical information systems(GIS).Compressional settings host some of the most significant hydrocarbon-bearing basins and 36% of inland CO2 emissions but,to date,large-scale CCS facilities in compressional basins are concentrated in North America and the Middle East only.Our source-to-sink tool allows identifying five high-priority regions for prospective CCS development in compressional basins:North America,north-western South America,south-eastern Europe,the western Middle East and western China.We present a study of the characteristics of these areas in terms of CO2 emissions and CO2 storage potential.Additionally,we conduct a detailed case-study analysis of the Sichuan Basin(China),one of the compressional basins with the greatest CO2 storage potential.Our results indicate that compressional basins will have to play a critical role in the future of CCS if this technology is to be implemented worldwide.

Compressional Deformation in Indentation Process for Microlens Array Mold

The structure of a microlens array( MLA) can be formed on copper by an indentation process which is a new manufacture approach we applied here instead of a traditional method to test the material property,thereby work time can be saved. Single-indentation and multi-indentation are both conducted to generate a single dimple and dimples array,namely micro lens and MLA. Based on finite element simulation method,factors affecting the form accuracy,such as springback at the compressed area of one single dimple and compressional deformation at the adjacent area of dimples arrays,are determined,and the results are verified by experiments under the same conditions. Meanwhile,indenter compensation method is proposed to improve form accuracy of single dimple,and the relationship between pitch and compressional deformation is investigated by modelling seven sets of multi-indentations at different pitches to identify the critical pitch for the MLA's indentation processing. Loads and cross-sectional profiles are measured and analyzed to reveal the compressional deformation mechanism. Finally,it is found that MLA at pitches higher than 1. 47 times of its diameter can be manufactured precisely by indentation using a compensated indenter.

Compressional elastic wave velocities of serpentinized pyroxenite at high pressures and high temperatures and its geological significance

Center for Analysis and Prediction, China Seismological Bureau, Beijing 100036, China 2) Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550002,

Compressional origin of the Aegean Orogeny,Greece

The Aegean Sea area is thought to be an actively extending back-arc region,north of the present day Hellenic volcanic arc and north-dipping subduction zone in the Eastern Mediterranean.The area shows extensive normal faulting,ductile‘extensional’shear zones and extensional S-C fabrics throughout the islands that have previously been related to regional Aegean extension associated with slab rollback on the Hellenic Subduction Zone.In this paper,we question this interpretation,and suggest the Cenozoic geodynamic evolution of the Aegean region is associated with a Late Cretaceous-Eocene NE-dipping subduction zone that was responsible for continentcontinent collision between Eurasia and Adria-Apulia/Cyclades.Exhumation of eclogite and blueschist facies rocks in the Cyclades and kyanite-sillimanite grade gneisses in the Naxos core complex have pressures that are far greater than could be accounted for purely by lithospheric extension and isostatic uplift.We identify four stages of crustal shortening that affected the region prior to regional lithospheric extension,herein called the Aegean Orogeny.This orogeny followed a classic Wilson cycle from early ophiolite obduction(ca.74 Ma)onto a previously passive continental margin,to attempted crustal subduction with HP eclogite and blueschist facies metamorphism(ca.54-45 Ma),through crustal thickening and regional kyanite-sillimanite grade Barroviantype metamorphism(ca.22-14 Ma),to orogenic collapse(<14 Ma).At least three periods of‘extensional’fabrics relate to:(1)Exhumation of blueschists and eclogite facies rocks showing tight-isoclinal folds and top-NE,base-SW fabrics,recording return flow along a subduction channel in a compressional tectonic setting(ca.50-35 Ma).(2)Extensional fabrics within the core complexes formed by exhumation of kyanite-and sillimanite gneisses showing thrust-related fabrics at the base and‘extensional’fabrics along the top(ca.18.5-14 Ma).(3)Regional ductile-brittle‘extensional’fabrics and low-angle normal faulting related to the North Cycladic Detachment(NCD)and the South(West)Cycladic Detachment(WCD)during regional extension along the flanks of a major NW-SE anticlinal fold along the middle of the Cyclades.Major low-angle normal faults and ductile shear zones show symmetry about the area,with the NE chain of islands(Andros,Tinos,Mykonos,Ikaria)exposing the NE-dipping NCD with consistent top-NE ductil e fabrics along 200 km of strike.In contrast,from the Greek mainland(Attica)along the SE chain of islands(Kea,Kythnos,Serifos)a SW-dipping low-angle normal fault and ductile shear zone,the WCD is inferred for at least 100 km along strike.Islands in the middle of the Cyclades show deeper structural levels including kyanite-and sillimanite-grade metamorphic core complexes(Naxos,Paros)as well as Variscan basement rocks(Naxos,Ios).The overall structure is an~100 km wavelength NW-SE trending dome with low-angle extensional faults along each flank,dipping away from the anticline axis to the NE and SW.Many individual islands show post-extensional large-scale folding of the low-angle normal faults around the domes(Naxos,Paros,Ios,Sifnos)indicating a post-Miocene late phase of E-W shortening.

Intraplate Strike-Slip Reactivation of the Sinnyeong Fault in the Cretaceous Gyeongsang Basin, Korea, Due to the Concentration of Later Compressional Stress

This study focuses on the geometry and kinematics of the Sinnyeong Fault which is the most conspicuous fault among the WNW-trending Gaeum Fault System in the Gyeongsang Basin,SE Korea. The fault is traced for over ca.70 kmand has a consistent WNW-trending strike with a nearly vertical dip. It has an asymmetric fault damage zone of several meters to several tens of meters in width and a several meter-thick fault core. Its main movement is interpreted as sinistral-reverse oblique-slip or sinistral strike-slip under NE-SW compressional stress regime, although it could have experienced other faultings with different senses before/after this movement. Cylindrical folds, having the NW-trending fold axes of low angle plunge, are only observed along the southern damage zone of the fault with a continuous narrow width of several tens of meters. It is thus interpreted that the formation of the folds and sinistral movement of the fault were almost contemporaneously generated due to the concentration of the regional NE-SW compressional stress along pre-existing WNW-trending faults or densely populated fracture zone in a relatively stable intraplate region.

Study on Calculation Method of Compressional Velocities Based on Field Well Logs

In the past, most of the studies for compressional velocities are based on experimental measurements, which lack the support of field data. The purpose of this study is to estimate the compressional velocities based on well log data of delta front subfacies of Lower Tertiary ages of Ji-Dong oil field, China. At initial stage, we have chosen the well log parameters (effect factors) which strongly influence on compressional velocities and established a new modified equation for compressional velocities, which is based on these effect factors. Then Gardner, De-hua Han and this newly established equation were utilized to calculate the compressional velocities in each well. Finally, Least-square regression was carried out to check the fitting of each equation. Regression results clearly indicate that our purposed equation shows better fitting as compared to Gardner and De-hua Han equations.

The effect of phase transition on the compressional wave velocity for a trachybasalt at high temperature and high pressure

Compressional wave velocities in a trachybasalt, from Yichuan County, Henan Province, have been measured at 2.0 GPa and up to 1 350℃ in a YJ-3000 t cubic-anvil highpressure apparatus. The run products have been gained at the same pressure but different temperatures. The observation of the thin sections of the run products indicates that, corresponding to the variation of the compressional wave velocity in the trachybasalt, the phase transition has taken place. The relationship between the change of the compressional wave velocity and the hydrous mineral dehydration, solid-solid phase transformation and partial melting has been discussed. The experimental data presented here are of great importance to elucidating the geological process in the earth’s interior.

Sedimentary Facies, Sequence Stratigraphic Patterns in Pre-Cenozoic Inland Compressional Basin: Example from Early Yanshanian Succession of Eastern Yihezhuang Salient, Jiyang Depression, Bohai Bay Basin, China

To improve the success rate of locating hydrocarbon reservoirs in pre-Cenozoic inland compressional basins, taking the Early Yanshanian succession of eastern Yihezhuang salient as an example, this paper studied the sedimentary facies and sequence stratigraphic patterns. First, through seismic profiles, well logs, cores and outcrops, the sequence framework was established and internal sedimentary facies were identified. Further, according to analysis of single-wells and connecting-wells, the vertical evolution and horizontal distribution of sedimentation inside the sequence frameworks were discussed. The following results were acquired:(1) meandering river characterized by dual structures superposing each other was developed, and the dual structures can be further divided into three kinds;(2) the entire Early Yanshanian succession was interpreted as one first-order sequence, composed of three third-order sequences, including SQ-Fz1, SQ-Fz2 and SQ-St from bottom to top. Each third-order sequence can be further divided into three system tracts;(3) in different system tracts, different types of dual structures developed separately, and sedimentary bodies showed different horizontal distribution scales and vertical superposition patterns. Finally, the model of sequence stratigraphic patterns was established. This study enhanced the use of sequence stratigraphy to inland tectonically active basins, and would be helpful to predict reservoirs in pre-Cenozoic residual basins.

Simultaneous inversion of layered compressional velocity and shear velocity by using plane wave seismogram

A layer-stripping method is presented for simultaneous inversion of compressional velocity and shear velocity in layered medium from single precritical-incident-angle data of P-P and P-SV plane wave seismogram. A finite bandwidth algorithm is provided and results obviously better than previous research work are obtained by the numerical experiments for band-limited seismogram and synthetic data including noise.

Leaky modes and their contributions to the compressional head wave in a borehole excited by a dipole source

A method of studying the contributions of leaky modes to the wave field is presented based on the analysis of the Riemann surface structure of the characteristic function, and the sensitivities of con- tributions to various factors of interest are examimed. Numerical results show that their contributions to the compressional head wave are related to the distributions of complex poles on (-1, -1) and (0, -1) Riemann sheets on the frequency-wavenumber (ω - k) plane. For fast formations, their contributions are small, while for slow formations with large Poisson’s ratio, their contributions are large because of those complex poles with small imaginary parts near the compressional vertical branch cut. The decaying factor of the contributions of leaky modes is approximately proportional to 1/distance2.

A multi-feature-based intelligent redundancy elimination scheme for cloud-assisted health systems

Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud-assisted health systems.Deduplication eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple duplicates.Delta compression is usually regarded as a complementary technique to deduplication to further remove the redundancy of similar blocks,but our observations indicate that this is disobedient when data have sparse duplicate blocks.In addition,there are many overlapped deltas in the resemblance detection process of post-deduplication delta compression,which hinders the efficiency of delta compression and the index phase of resemblance detection inquires abundant non-similar blocks,resulting in inefficient system throughput.Therefore,a multi-feature-based redundancy elimination scheme,called MFRE,is proposed to solve these problems.The similarity feature and temporal locality feature are excavated to assist redundancy elimination where the similarity feature well expresses the duplicate attribute.Then,similarity-based dynamic post-deduplication delta compression and temporal locality-based dynamic delta compression discover more similar base blocks to minimise overlapped deltas and improve compression ratios.Moreover,the clustering method based on block-relationship and the feature index strategy based on bloom filters reduce IO overheads and improve system throughput.Experiments demonstrate that the proposed method,compared to the state-of-the-art method,improves the compression ratio and system throughput by 9.68%and 50%,respectively.

Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block-GAN

In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may manifest.This necessitates the restoration of the image to its original quality.The challenge lies in regenerating significantly compressed images into a state in which these become identifiable.Therefore,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks(GAN).The generator in this network is based on theU-Net architecture.It features a newhourglass structure that preserves the characteristics of the deep layers.In addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)loss.HF loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents features.This can enhance the performance in the high-frequency region.In contrast,LF loss is used to handle the low-frequency region.The two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency regions.Consequently,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are generated.This study represents a significant improvement over previous research in terms of the image resolution performance.

Enhanced prediction of anisotropic deformation behavior using machine learning with data augmentation

Mg alloys possess an inherent plastic anisotropy owing to the selective activation of deformation mechanisms depending on the loading condition.This characteristic results in a diverse range of flow curves that vary with a deformation condition.This study proposes a novel approach for accurately predicting an anisotropic deformation behavior of wrought Mg alloys using machine learning(ML)with data augmentation.The developed model combines four key strategies from data science:learning the entire flow curves,generative adversarial networks(GAN),algorithm-driven hyperparameter tuning,and gated recurrent unit(GRU)architecture.The proposed model,namely GAN-aided GRU,was extensively evaluated for various predictive scenarios,such as interpolation,extrapolation,and a limited dataset size.The model exhibited significant predictability and improved generalizability for estimating the anisotropic compressive behavior of ZK60 Mg alloys under 11 annealing conditions and for three loading directions.The GAN-aided GRU results were superior to those of previous ML models and constitutive equations.The superior performance was attributed to hyperparameter optimization,GAN-based data augmentation,and the inherent predictivity of the GRU for extrapolation.As a first attempt to employ ML techniques other than artificial neural networks,this study proposes a novel perspective on predicting the anisotropic deformation behaviors of wrought Mg alloys.

Atomistic evaluation of tension–compression asymmetry in nanoscale body-centered-cubic AlCrFeCoNi high-entropy alloy

The tension and compression of face-centered-cubic high-entropy alloy(HEA) nanowires are significantly asymmetric, but the tension–compression asymmetry in nanoscale body-centered-cubic(BCC) HEAs is still unclear. In this study,the tension–compression asymmetry of the BCC Al Cr Fe Co Ni HEA nanowire is investigated using molecular dynamics simulations. The results show a significant asymmetry in both the yield and flow stresses, with BCC HEA nanowire stronger under compression than under tension. The strength asymmetry originates from the completely different deformation mechanisms in tension and compression. In compression, atomic amorphization dominates plastic deformation and contributes to the strengthening, while in tension, deformation twinning prevails and weakens the HEA nanowire.The tension–compression asymmetry exhibits a clear trend of increasing with the increasing nanowire cross-sectional edge length and decreasing temperature. In particular, the compressive strengths along the [001] and [111] crystallographic orientations are stronger than the tensile counterparts, while the [110] crystallographic orientation shows the exactly opposite trend. The dependences of tension–compression asymmetry on the cross-sectional edge length, crystallographic orientation,and temperature are explained in terms of the deformation behavior of HEA nanowire as well as its variations caused by the change in these influential factors. These findings may deepen our understanding of the tension–compression asymmetry of the BCC HEA nanowires.

Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

Given their numerous functional and architectural benefits,such as improved bearing capacity and increased resistance to elastic instability modes,cold-formed steel(CFS)built-up sections have become increasingly developed and used in recent years,particularly in the construction industry.This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations(backto-back,face-to-face,and box).These columns were joined by double-row rivets for the back-to-back and box configurations,whereas they were welded together for the face-to-face design.The built-up columns were filled with ordinary concrete of good strength.Finite element models were applied,using ABAQUS software,to assess mechanical performance and study the influence of assembly techniques on the behavior of cold-formed columns under axial compression.Analytical approaches based on Eurocode 3 and Eurocode 4 recommendations for un-filled and concrete-filled columns respectively were followed for the numerical analysis,and concrete confinement effects were also considered per American Concrete Institute(ACI)standards for face-to-face and box configurations.The obtained results indicated a good correlation between the numerical results and the proposed analytical methodology which did not exceed 8%.The failure modes showed that the columns failed due to instabilities such as local and global buckling.

An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model output.Extensive experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOPs with a degradation of just 0.11% accuracy.

Simulation of Dynamic Recrystallization in 7075 Aluminum Alloy Using Cellular Automaton

The evolution of microstructure during hot deformation is key to achieving good mechanical properties in aluminum alloys.We have developed a cellular automaton(CA) based model to simulate the microstructural evolution in 7075 aluminum alloy during hot deformation.Isothermal compression tests were conducted to obtain material parameters for 7075 aluminum alloy,leading to the establishment of models for dislocation density,nucleation of recrystallized grains,and grain growth.Integrating these aspects with grain topological deformation,our CA model effectively predicts flow stress,dynamic recrystallization(DRX) volume fraction,and average grain size under diverse deformation conditions.A systematic comparison was made between electron back scattered diffraction(EBSD) maps and CA model simulated under different deformation temperatures(573 to 723 K),strain rates(0.001 to 1 s^(-1)),and strain amounts(30% to 70%).These analyses indicate that large strain,high temperature,and low strain rate facilitate dynamic recrystallization and grain refinement.The results from the CA model show good accuracy and predictive capability,with experimental error within 10%.

Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease diagnosis.One promising avenue involves the use of chest X-Rays,which are commonly utilized in radiology.To fully exploit their potential,researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems.However,constructing and compressing these systems presents a significant challenge,as it relies heavily on the expertise of data scientists.To tackle this issue,we propose an automated approach that utilizes an evolutionary algorithm(EA)to optimize the design and compression of a convolutional neural network(CNN)for X-Ray image classification.Our approach accurately classifies radiography images and detects potential chest abnormalities and infections,including COVID-19.Furthermore,our approach incorporates transfer learning,where a pre-trainedCNNmodel on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting COVID-19.This method can help reduce the amount of labeled data required for the task and enhance the overall performance of the model.We have validated our method via a series of experiments against state-of-the-art architectures.